grseb9s Goto Github PK
Name: GRS
Type: Organization
Bio: Geosciences & Remote Sensing
Location: ECUT
Name: GRS
Type: Organization
Bio: Geosciences & Remote Sensing
Location: ECUT
Spatial Generative Adversarial Networks
Implementation of spatial transformer networks in keras 2.0 using tensorflow 1.0 as backend.
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012
specio: Python input/output for spectroscopic files
Python module for hyperspectral image processing
A software package is built for display and classification of Hyperspectral Images captured byIMS-1 HySI sensor has been developed using SAM.The construction and display of the 3-D cube by considering all the 64 bands of image at a time. The identification of classes in the Hyperspectral Image using a supervised classification algorithm called the Spectral Angle Mapper Algorithm. Results are obtained to read and reorganize multiple 2-D datasets into a single compact 3D dataset cube.Thematic Information Extraction — Supervised Classification Remotely sensed data may be analyzed to extract use- ful thematic information. This transforms the data into in- formation. For example, themes may include land-cover, water bodies, and clouds. The classification may be per- formed using supervised, unsupervised and fuzzy set clas- sification approaches. In a supervised image classification, the identity and lo- cation of some of the land-cover types should be known beforehand through a combination of fieldwork, analy- sis of aerial photography, maps, and personal experience. The analyst attempts to locate sites in the remotely sensed data that represent homogeneous examples of these known land-cover types. These areas are commonly referred to as training sites because the spectral characteristics of these known areas are used to train the classification algorithm for eventual land-cover mapping of the remainder of the image. Multivariate statistical parameters such as means, standard deviations, and covariance matrices are calculated for each training site. Every pixel both inside and outside these training sites is then evaluated and assigned to the class where it has the highest likelihood of being a mem- ber. This is often referred to as hard classification because a pixel is assigned to only one class (e.g., forest), even though the sensor records the radiant flux from a mixture of biophysical materials, for example: 10% bare soil, 20% scrub shrub, 70% forest.
C++ Library that reads the splib06a file, which is a custom binary spectral reflectance database file created by USGS
Development of a led-arduino-camera system for hyperspectral imaging
A Hyperspectral Visualization and Analysis Engine for iOS
CLI utilities to perform linear spectral unmixing of Hyperspectral images based on spectral signature of pure endmembers.
Hyperspectral skin masking/segmentation (single-pass, line-by-line)
:exclamation: This is a read-only mirror of the CRAN R package repository. spectrolab — Class and Methods for Hyperspectral Data. Homepage: https://github.com/annakat/spectrolab
SpecVis - Visualization and classification of 2D chemical and hyperspectral images.
Sparsity Promoting Iterated Constrained Endmembers
Spike detection
Example simulation of spiking networks in Tensorflow adapted from a Matlab example
A research project for treating neural networks as cellular automata (an alternative to lstm)
SPLATNet: Sparse Lattice Networks for Point Cloud Processing (CVPR2018)
Automatically exported from code.google.com/p/shooter-player
Lightweight plotting for geospatial analysis in PySAL
Sparsity Preserving Projection, a feature extraction algorithm in Pattern Recognition area
SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Tensor decomposition with directed factor level sparity
R package: spup - Spatial Uncertainty Propagation Analysis
Spectral methods for Uncertainty Quantification
multilevel spatially-correlated variance components models
Official repository for Spyder - The Scientific PYthon Development EnviRonment
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.